Effect of Twisted-Yarn Architecture on Pressure and Proximity Sensing Characteristics of Textile Capacitive Sensors for Robotic Skin

Abstract:Textile-integrated capacitive sensors offer flexible and conformable tactile sensing for wearable electronics and human-robot interaction; however, the influence of yarn-level architecture on capacitive transduction characteristics remains insufficiently quantified. This work presents a textile capacitive sensing platform based on silver-coated yarns coated with polydimethylsiloxane and assembled into one-, two-, and four-layer twisted configurations. The influence of effective electrode overlap area and inter-fiber separation on the capacitive response is systematically investigated, enabling architecture-dependent tuning of pressure and proximity sensing characteristics. Pressure was calculated using the localized single-fiber contact area, corresponding to stresses of 0.4-3.9 MPa. Increasing the layer number improved mechanical strength and sensing performance: elongation at break increased from 37.5% to 62.5% and 85.0%, while the maximum load increased from 23.3 to 42.7 and 89.7 N. Sensitivity increased with layer number and frequency, reaching 0.1331 MPa$^{-1}$ for the four-layer sensor at 100 kHz. The four-layer configuration also exhibited low hysteresis, minimal thermal drift from 25 to 90 $^\circ$C, and stable operation over 15,000 cycles. Proximity detection ranges of 60, 50, and 40 mm were obtained for the one-, two-, and four-layer sensors, respectively, revealing an architecture-dependent sensitivity-range trade-off. A 4$\times$4 textile sensing array enabled spatial contact mapping, while robotic-arm integration demonstrated real-time touch and proximity detection with an end-to-end robotic system latency (from detection to robot reaction) of 403 ms. The results establish yarn architecture as a tunable design parameter governing the measurement characteristics of textile-integrated capacitive sensing systems.

10 pages. Submitted to IEEE Transactions on Instrumentation and Measurement

Robotics (cs.RO); Instrumentation and Detectors (physics.ins-det)

arXiv:2608.14406 [cs.RO]

(or arXiv:2608.14406v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2608.14406 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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